Passives without actives: evidence from verbless complement clauses in Spanish

This paper proposes a constructionist analysis à la Goldberg (1995, 2003, 2006) of passive verbless configurations in Spanish lacking a felicitous active counterpart.Under the paradigmatic – rather than syntagmatic – view of passives invoked in this paper, configurations of the type in (1) above, attested with a number of verba cogitandi et dicendi, are handled as instances of the Impersonal Subjective-Transitive construction, whose general skeletal meaning is X (NP1) attributed Y (XPCOMP) by Z (NP2) in a direct, categorical way. Moreover, the analysis proposed here also provides a satisfactory account of the distribution of grammatical subjects and the XPCOMPs, while also capturing the commonalities with “regular” passives (i.e. those with a felicitous active counterpart). In addition, Spanish passive verbless complement configurations with se dice (‘is said’) are shown to illustrate a three-point continuum consisting of (i) non-grammaticalized configurations with an active counterpart, (ii) non-grammaticalized configurations without an active counterpart, and (iii) grammaticalized configurations without an active counterpart. From a synchronic point of view, the structural and semantico-pragmatic properties exhibited by the lower-level lo que se dice XPFOCUS construction, involving a focusing/emphasizer subjunct function (e.g. verdaderamente ‘really’) as well as a reformulatory connective use (e.g. o sea ‘that is’, en otras palabras ‘in other words’) appear to point to an early process of grammaticalization, exhibiting decategorialization as well as generalization of meaning in conjunction with a prominent increase in pragmatic function and subjectification (cf. Traugott 1988, 1995a, 1995b, 2003).

Visual Fixation for 3D Video Stabilization

Visual fixation is employed by humans and some animals to keep a specific 3D location at the center of the visual gaze. Inspired by this phenomenon in nature, this paper explores the idea to transfer this mechanism to the context of video stabilization for a handheld video camera. A novel approach is presented that stabilizes a video by fixating on automatically extracted 3D target points. This approach is different from existing automatic solutions that stabilize the video by smoothing. To determine the 3D target points, the recorded scene is analyzed with a stateof- the-art structure-from-motion algorithm, which estimates camera motion and reconstructs a 3D point cloud of the static scene objects. Special algorithms are presented that search either virtual or real 3D target points, which back-project close to the center of the image for as long a period of time as possible. The stabilization algorithm then transforms the original images of the sequence so that these 3D target points are kept exactly in the center of the image, which, in case of real 3D target points, produces a perfectly stable result at the image center. Furthermore, different methods of additional user interaction are investigated. It is shown that the stabilization process can easily be controlled and that it can be combined with state-of-theart tracking techniques in order to obtain a powerful image stabilization tool. The approach is evaluated on a variety of videos taken with a hand-held camera in natural scenes.